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fixup

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This commit is contained in:
Philippe Tillet
2019-08-06 16:44:16 -07:00
parent 5efdb7978e
commit cf256a636c
7 changed files with 42 additions and 39 deletions
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17
examples/cpp/dot.cpp
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@@ -6,6 +6,7 @@
#include "triton/driver/stream.h"
#include "triton/dnn/dot.h"
#include "triton/tools/bench.hpp"
#include "triton/external/half.hpp"
#include "cuda.h"
template<class T>
@@ -25,7 +26,7 @@ struct perf_t {
perf_t do_bench(triton::driver::stream* stream, bool AT, bool BT, int32_t M, int32_t N, int32_t K){
typedef float NumericT;
typedef half NumericT;
std::string ty = "half";
size_t dt_nbytes = sizeof(NumericT);
triton::driver::context* context = stream->context();
@@ -34,11 +35,11 @@ perf_t do_bench(triton::driver::stream* stream, bool AT, bool BT, int32_t M, int
std::vector<NumericT> hb(K*N);
srand(0);
for(size_t i = 0; i < ha.size(); i++)
ha[i] = (NumericT)rand()/RAND_MAX;
ha[i] = static_cast<NumericT>((double)rand()/RAND_MAX);
for(size_t i = 0; i < hb.size(); i++)
hb[i] = (NumericT)rand()/RAND_MAX;
hb[i] = static_cast<NumericT>((double)rand()/RAND_MAX);
for(size_t i = 0; i < hc.size(); i++)
hc[i] = 0;
hc[i] = static_cast<NumericT>((double)0);
triton::driver::buffer* dc = triton::driver::buffer::create(context, hc.size()*dt_nbytes);
triton::driver::buffer* da = triton::driver::buffer::create(context, ha.size()*dt_nbytes);
triton::driver::buffer* db = triton::driver::buffer::create(context, hb.size()*dt_nbytes);
@@ -48,7 +49,7 @@ perf_t do_bench(triton::driver::stream* stream, bool AT, bool BT, int32_t M, int
stream->synchronize();
triton::dnn::dot dot(M, N, K, AT, BT, ty, ty, 8, 8, 8);
// benchmark triton
double triton_ns = triton::tools::bench([&]() { dot.enqueue(stream, {da, db, dc}, triton::dnn::FULL_TUNING);}, stream);
double triton_ns = triton::tools::bench([&]() { dot.enqueue(stream, {da, db, dc}, triton::dnn::NO_TUNING);}, stream);
// benchmark cublas
// NumericT alpha = 1;
// NumericT beta = 0;
@@ -73,10 +74,10 @@ perf_t do_bench(triton::driver::stream* stream, bool AT, bool BT, int32_t M, int
// test
stream->read(dc, true, 0, hc);
std::vector<float> rc(hc.size());
std::vector<NumericT> rc(hc.size());
dot.cpu_ref(rc, ha, hb);
for(size_t i = 0; i < M*N; i++)
if(!std::isnan(hc[i]) && std::abs(hc[i] - rc[i])/std::max(hc[i], rc[i]) > 1e-4){
if(std::isnan(hc[i]) || std::abs(hc[i] - rc[i])/std::max(hc[i], rc[i]) > 1e-4){
std::cout << i << " " << hc[i] << " " << rc[i] << std::endl;
exit(EXIT_FAILURE);
}
@@ -111,7 +112,7 @@ int main() {
std::vector<config_t> configs = {
// {false, false, 8192, 512, 512},
// {false, true, 8192, 8192, 8192}
{true, true, 128, 128, 128},
{false, true, 128, 128, 128},
// {false, true, 32768, 256, 512}
// {true, false, 8192, 512, 512},
// {true, true, 8192, 512, 512}

4
include/triton/dnn/dot.h
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@@ -42,9 +42,9 @@ public:
size_t M, size_t N, size_t K){
for(size_t m = 0; m < M; m++)
for(size_t n = 0; n < N; n++){
T acc = 0;
T acc = static_cast<T>((double)0);
for(size_t k = 0; k < K; k++)
acc += (AT?a[k + m*K]:a[m + k*M]) * (BT?b[n + k*N]:b[k + n*K]);
acc = acc + (AT?a[k + m*K]:a[m + k*M]) * (BT?b[n + k*N]:b[k + n*K]);
c[m + n*M] = acc;
}
}

1
include/triton/runtime/jit.h
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@@ -73,7 +73,6 @@ public:
optimize_dot.run(module);
optimize_trans.run(module);
optimize_dce.run(module);
// ir::print(module, std::cout);
}
void target_dependent(ir::module &module) {

40
lib/codegen/tune.cpp
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@@ -194,7 +194,6 @@ std::vector<ir::metaparameter *> tune::get_params(ir::module &mod) {
for(ir::instruction *i : block->get_inst_list())
for(auto &x: params_[i])
if(seen.insert(x.second).second && !x.second->has_value()){
// std::cout << i->get_name() << " " << x.first << std::endl;
result.push_back(x.second);
}
@@ -291,28 +290,29 @@ void tune::run(ir::module &mod) {
}
// initialize grids
// for(ir::instruction *i: grids_){
// auto shapes = i->get_type()->get_tile_shapes();
// for(size_t k = 0; k < shapes.size(); k++)
// if(shapes[k]->get_value() == 1) {
// if(fragments_.at({i, k}) == STRIDED_SCAN){
// params_.at(i).at("nts.d" + std::to_string(k))->set_value(1);
// params_.at(i).at("mts.d" + std::to_string(k))->set_value(1);
// }
// if(fragments_.at({i, k}) == HMMA_FRAGMENT_C){
// params_.at(i).at("fpw.d" + std::to_string(k))->set_value(1);
// params_.at(i).at("wpt.d" + std::to_string(k))->set_value(1);
// }
// }
// }
}
void tune::init(ir::module &mod) {
for(ir::function *fn: mod.get_function_list()){
std::map<ir::metaparameter*, ir::instruction*> references;
create_grids(grids_, references, fn);
}
for(ir::instruction *i: grids_){
auto shapes = i->get_type()->get_tile_shapes();
for(size_t k = 0; k < shapes.size(); k++)
if(shapes[k]->get_value() == 1) {
if(fragments_.at({i, k}) == STRIDED_SCAN){
params_.at(i).at("nts.d" + std::to_string(k))->set_value(1);
params_.at(i).at("mts.d" + std::to_string(k))->set_value(1);
}
if(fragments_.at({i, k}) == HMMA_FRAGMENT_C){
params_.at(i).at("fpw.d" + std::to_string(k))->set_value(1);
params_.at(i).at("wpt.d" + std::to_string(k))->set_value(1);
}
}
}
}
void tune::init(ir::module &mod) {
num_threads_ = get_req_num_threads(grids_.front());
}
@@ -407,7 +407,9 @@ bool tune::check_constraints(std::map<ir::value *, std::vector<std::string>> &er
else {
ir::metaparameter *fpw = params_[i]["fpw.d" + strk];
ir::metaparameter *wpt = params_[i]["wpt.d" + strk];
multiple = fpw->get_value()*wpt->get_value()*8;
multiple = fpw->get_value()*wpt->get_value();
if(k < 2)
multiple *= 8;
}
if(shapes[k]->get_value() % multiple != 0)
errors[i].push_back("for dim " + strk + ": shape (" + to_string(shapes[k]->get_value()) + ")"

4
lib/dnn/base.cpp
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@@ -62,11 +62,11 @@ std::pair<base*, rt::jit*> base::get_profile_impl(driver::stream *stream, std::v
jit->add_module(name_.c_str(), src.c_str(), best.params);
}
else{
// params_t params = heuristics();
params_t params = heuristics();
// params_t params = jit->get_valid(name_.c_str(), src.c_str());
// params_t params = {4, 1, 32, 4, 1, 32, 4, 4, 4, 1, 1, 16, 32, 16, 4, 4, 4, 4, 1}; //NT
// params_t params = {4, 1, 32, 4, 32, 4, 4, 4, 1, 1, 16, 32, 16, 1, 4, 4, 4, 4, 4, 1}; //NN
params_t params = {4, 32, 4, 1, 32, 4, 4, 4, 1, 1, 16, 1, 32, 16, 4, 4, 4, 4, 4, 1}; // TT
// params_t params = {4, 32, 4, 1, 32, 4, 4, 4, 1, 1, 16, 1, 32, 16, 4, 4, 4, 4, 4, 1}; // TT
jit->add_module(name_.c_str(), src.c_str(), params);
}
triton::driver::kernel* kernel = jit->get_function(name_.c_str());

9
lib/dnn/dot.cpp
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@@ -74,8 +74,8 @@ void dot::enqueue_impl(driver::stream *stream, driver::kernel *kernel,
void dot::triton_c_src(std::ostream &os) const {
std::string AS0 = "TM", AS1 = "TK";
std::string BS0 = "TK", BS1 = "TN";
std::string XAS0 = "TM", XAS1 = "TK/1", XAS2 = "1";
std::string XBS0 = "TK/1", XBS1 = "1", XBS2 = "TN";
std::string XAS0 = "TM", XAS1 = "TK", XAS2 = "1";
std::string XBS0 = "TK", XBS1 = "1", XBS2 = "TN";
std::string bca0 = "[newaxis, :]", bca1 = "[:, newaxis]";
std::string bcb0 = "[:, newaxis]", bcb1 = "[newaxis, :]";
std::string lda0 = "*lda", lda1 = "";
@@ -105,11 +105,12 @@ void dot::triton_c_src(std::ostream &os) const {
std::string align_ldb_str = "multiple_of(" + std::to_string(align_ldb_) + ")";
std::string res =
R"(
const tunable int TM = {32};
const tunable int TN = {32};
const tunable int TM = {16, 32, 64, 128};
const tunable int TN = {16, 32, 64, 128};
const tunable int TK = {32};
const tunable int GZ = {1};
void matmul(restrict read_only align(16) )" + a_ty_ + R"( *A,
restrict read_only align(16) )" + b_ty_ + R"( *B,
restrict read_only align(16) float *C,

6
lib/runtime/jit.cpp
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@@ -37,13 +37,13 @@ void parallel_loop_nest(std::vector<size_t> const & ranges,
size_t D = ranges.size();
std::vector<size_t> values(D, 0);
// thread pools
ThreadPool pool(nthreads);
// ThreadPool pool(nthreads);
// Start with innermost loop
size_t i = D - 1;
while(true){
// Execute function
pool.enqueue(f,values);
// f(values);
// pool.enqueue(f,values);
f(values);
while(values[i]++ == ranges[i] - 1){
if(i == 0)
return;